This thesis is interested in evaluating how the market power of insurers and hospitals in sub-markets determines the prices insurers and hospitals negotiate for hospital care. New Hampshire provides a carrier-specific prices by hospital for particular medical procedures and services on the NH HealthCost website and therefore provides a unique case-study of insurer versus hospital market power. The pie charts below are taken from the NH Insurance Department 2017 Final Report of Health Care Premium and Claim Cost Drivers (published November 2018) and illustrate relevant information about the insurance market in New Hampshire.
To obtain some data on hospital costs, I copy and pasted tables from NH HealthCost for particular medical procedures and services into Excel spreadsheets (one for each medical procedure/service). At first, I attempted to mimic the 8 selected services analyzed in Cooper et al. (2018) (Inpatient, Hip Replacement, Knee Replacement, Cesarean Section, Vaginal Delivery, PTCA, Colonoscopy, and Lower Limb MRI), but the website only had data for colonoscopies and MRIs. I therefore chose 8 of my own procedures somewhat randomly: Arthroscopic Knee Surgery (outpatient), Diagnostic colonoscopy (outpatient), Colonoscopy with biopsy (outpatient), Colonoscopy with polyp removal (outpatient), MRI - Pelvis (outpatient), X-Ray - Ankle (outpatient), MRI - Knee (outpatient), Blood test for complete blood cell count (hemoglobin).
This allowed me to construct a data set containing the estimated price for each procedure and each provider-insurer combination for which data was available. The following boxplots depict the various distributions of estimated prices for each private insurer.
The following depict how prices vary across the state for the three major private insurers (Anthem NH, CIGNA, and Harvard Pilgrim).
A large part of the motivation behind this thesis is due to the existence of within-hospital variation of prices: for the exact same service, hospitals are able to charge different payers different amounts. Below are some visual examples to illustrate this variation between the three major private payers for the exact same service at the exact same hospital.
For hospitals which had a price range between insurers >$100 for ankle x-rays:
For hospitals which had a price range between insurers >$20 for blood tests:
The goal of this analysis is to determine whether there is a statistical difference between the prices hospitals charge Anthem, Harvard Pilgrim, and CIGNA in New Hampshire. That is, for the same service at the same hospital, is one insurer consistently paying a higher amount than the other two? In order to go about this, I want
eight_procedures %>%
count(provider_name) %>%
arrange(desc(n))
## # A tibble: 101 x 2
## provider_name n
## <chr> <int>
## 1 "Elliot Hospital " 36
## 2 "Exeter Hospital " 36
## 3 "Southern NH Medical Center " 35
## 4 "Mary Hitchcock Memorial Hospital " 32
## 5 "St. Joseph Hospital " 31
## 6 "Concord Hospital " 27
## 7 "Memorial Hospital " 26
## 8 "Parkland Medical Center " 26
## 9 "Portsmouth Regional Hospital " 26
## 10 "Steward Medical Group " 26
## # ... with 91 more rows